Simulations of past and future climate change remain limited by uncertainties, especially at scales relevant to policymaking. To provide more actionable information for risk assessments, climate storylines have become a popular approach to complement probabilistic event attribution and climate projection. According to the latest IPCC-WG1 report, “the term storyline is used both in connection to scenarios or to describe plausible trajectories of weather and climate conditions or events”. Storylines are used to “explore uncertainties in climate change and natural climate variability, to develop and communicate integrated and context-relevant regional climate information, and to address issues with deep uncertainty, including low-likelihood, high-impact outcomes”.
Several flavours of storylines exist. One method, event-based storylines, employs model simulations to attribute and project the climate signal in specific weather events, using forcing and boundary conditions from different past, present, and possible future climates. This approach quantifies and explores thermodynamic climate effects while eliminating uncertain dynamical changes by constraining (nudging) the winds to reproduce the observed circulation. Another storyline method, dynamical storylines, extracts physically plausible (regional) climate change scenarios, conditional upon robustly simulated aspects of the climate system such as the large-scale dynamical response or the response of relevant climate modes, thereby disentangling the often-blurred multi-model mean response. Numerous storyline studies exist or are underway, ranging from global to regional (including pseudo-global-warming experiments) setups to local impacts, with both coupled or uncoupled (atmosphere or land-surface) models.
This session provides a forum to present and discuss the latest storyline-based climate research, thereby fostering exchanges in this fast-growing field. We invite contributions including but not limited to the approaches described above, using any analytical methods or modelling frameworks that seek to unravel climate change and, ultimately, provide actionable climate outcomes. Studies can range across spatial and temporal scales, and from fundamental considerations about the pros and cons of storyline approaches and how they relate to the probabilistic paradigm, to specific studies dealing with individual events, challenges, or other aspects of climate storylines.